![]() Nest Columns Select Note: This parameter is only available when the File Type parameter is set to "JSON". Compression Select Whether the input file is compressed in gzip format, BROTLI, BZ2, DEFLATE, RAW_DEFLATE, ZSTD or not compressed at all. File Type Select Choose whether you would like Matillion ETL to unload the data in a CSV, JSON, or PARQUET format. Selecting the file format will use the S3 Unload component's properties to define the file format. Additional file formats can be created using the Create File Format component. Format Select Choose from preset file formats available in your Snowflake database. Table name Text The table or view to unload to S3. For more information on using multiple schemas, see this article. The special value, will use the schema defined in the environment. Database Select Choose a database to create the new table in. Warehouse Select Choose a Snowflake warehouse that will run the load. Note: Storage integrations can be configured to support Amazon S3, Google Cloud Storage, or Microsoft Azure cloud storage regardless of the cloud provider that hosts your Snowflake account. To learn more about setting up a storage integration, read Storage Integration Setup Guide. Integrations must be set up in advance of selecting them in Matillion ETL. Storage integrations are required to permit Snowflake to read data from and write to a cloud storage location. Storage Integration Select Select the storage integration. Click Manage to edit or create new credentials in Manage Credentials. The special value,, uses the set of credentials specified in your Matillion ETL environment-this is the default value. Credentials Select Select your AWS credentials. More information can be found at CREATE STORAGE INTEGRATION. A storage integration is a Snowflake object that stores a generated identity and access management (IAM) entity for your external cloud storage, along with an optional set of permitted or blocked storage locations (Amazon S3, Google Cloud Storage, or Microsoft Azure). Storage Integration: Uses a Snowflake storage integration. ![]() Users can choose either:Ĭredentials: Uses AWS security credentials. Authentication Select Select the authentication method. Master Key Select The ID of the client-side encryption key you have chosen to use in the Encryption property. KMS Key ID Select The ID of the KMS encryption key you have chosen to use in the Encryption property. Read Using server-side encryption with Amazon S3-managed encryption keys (SSE-S3) to learn more. SSE S3: Encrypt the data according to a key stored on an S3 bucket. Read AWS Key Management Service (AWS KMS) to learn more. SSE KMS: Encrypt the data according to a key stored on KMS. Read Protecting data using client-side encryption to learn more. This property is available when using an existing Amazon S3 location for staging.Ĭlient Side Encryption: Encrypt the data according to a client-side master key. Encryption Select Decide how the files are encrypted inside the S3 bucket. All unloads are parallel and will use the maximum number of nodes available at the time. Each file will be named as the prefix followed by a number denoting which node this was unloaded from. File Prefix Text Filename prefix for unloaded data to be named on the S3 bucket. This works in the same manner as the Go button. When a user enters a forward slash character / after a folder name, a validation of the file path is triggered. S3 Object Prefix Text/Select The name of the file for data to be unloaded into. Otherwise, "Custom" can be chosen for the staging to be based on the component's properties. ![]() These stages must be created from your Snowflake account console. Stage Select Choose a predefined stage for your data. Properties Snowflake Properties Property Setting Description Name Text A human-readable name for the component. The user must type in the bucket they want to access or use a variable to load/unload to those structures.Set up cross-account access via AWS roles.To access an S3 bucket from a different AWS account, the following is required: However, S3 Unload sacrifices some of the added functionality that comes from Text Output pulling the data through the Matillion ETL instance (such as adding column headers to each file). Since S3 Unload unloads data in parallel directly from Amazon Redshift to S3, it tends to be faster than using Text Output. Creates files on a specified S3 bucket, and load them with data from a table or view.įor Snowflake users: by default, your data will be unloaded in parallel.įor Amazon Redshift users: your data will be unloaded in parallel by default, creating separate files for each slice on your cluster.įor Amazon Redshift users: this component is similar in effect to the Text Output component. ![]()
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